Presentation Type
Poster Presentation
In Person or Zoom Presentation
In-Person
Campus
Daytona Beach
Status
Student
Faculty/Staff Department
Human Factors and Behavioral Neurobiology
Student Year and Major
Junior , Human Factors Psychology
Organization, if requesting a table
EcoCAR
Invited Speaker Institution/Department
EcoCAR
Presentation Description/Abstract
Abstract Software-defined vehicles (SDVs) change after sale through over-the-air (OTA) updates. We define automotive sustainability as maximizing useful service from the materials, battery, and energy invested in a vehicle over it’s life cycle, in turn promoting long-term ecological balance. OTA updates advance this in three ways: extending service life, fixing defects remotely, and adding software that lowers energy use, such as off-peak charging recommendations. Energy features, however, save energy only when drivers notice, understand, and safely use them. Our focused literature review connects three findings: eco-driving feedback improves fuel economy by 6.6% on average, interface design shapes both that benefit and the visual distraction it causes, and drivers' mental models and trust degrade when a familiar system behaves unexpectedly, as it can after an update. This human factors research, supported by Embry-Riddle’s EcoCAR Innovation Challenge, evaluates OTA-delivered energy features: charging recommendations, efficiency and range displays, and eco-driving feedback on center and head-up displays. A feature matrix compares these features across 13 current SDVs using two criteria sets. Sustainability criteria record each feature's mechanism and the magnitude and source of its reported energy benefit. Human factors criteria assess available evidence against National Highway Traffic Safety Administration (2013) guidelines for minimizing visual-manual distraction, alongside usability heuristics, comprehensibility, and whether updates disclose what changed. A feature counts as improving sustainability without creating new safety or usability problems only if it satisfies both sets. Features that pass will inform the team's human-machine interface design for the 2026 Chevrolet Blazer EV.
Keywords
Software-defined vehicles, Over-the-air updates, Sustainability, Human factors, Mental models, Human-machine interface, Trust, Usability
Included in
Sustainability Without Limits: Over-the-air Updates in SDV's
Abstract Software-defined vehicles (SDVs) change after sale through over-the-air (OTA) updates. We define automotive sustainability as maximizing useful service from the materials, battery, and energy invested in a vehicle over it’s life cycle, in turn promoting long-term ecological balance. OTA updates advance this in three ways: extending service life, fixing defects remotely, and adding software that lowers energy use, such as off-peak charging recommendations. Energy features, however, save energy only when drivers notice, understand, and safely use them. Our focused literature review connects three findings: eco-driving feedback improves fuel economy by 6.6% on average, interface design shapes both that benefit and the visual distraction it causes, and drivers' mental models and trust degrade when a familiar system behaves unexpectedly, as it can after an update. This human factors research, supported by Embry-Riddle’s EcoCAR Innovation Challenge, evaluates OTA-delivered energy features: charging recommendations, efficiency and range displays, and eco-driving feedback on center and head-up displays. A feature matrix compares these features across 13 current SDVs using two criteria sets. Sustainability criteria record each feature's mechanism and the magnitude and source of its reported energy benefit. Human factors criteria assess available evidence against National Highway Traffic Safety Administration (2013) guidelines for minimizing visual-manual distraction, alongside usability heuristics, comprehensibility, and whether updates disclose what changed. A feature counts as improving sustainability without creating new safety or usability problems only if it satisfies both sets. Features that pass will inform the team's human-machine interface design for the 2026 Chevrolet Blazer EV.